Modern spreadsheet application programs generally provide sophisticated charting tools for graphically representing data. One such charting tool provides a drag-and-drop user interface (DDUI) that permits a user to populate a chart with data from a data source (e.g., a multi-dimensional database). The primary benefit of the charting DDUI is that the user can quickly change the data that is being presented in the chart. For example, a user can drag-and-drop an icon representing the data field containing the sales of widgets in Washington. The data in the data field will be used to populate the portion of the charting DDUI into which the data field icon was dropped. The user may then replace the icon with another data field icon to generate a chart of the sales of widgets in Oregon. Thus, the charting DDUI enables quick comparisons between various data, without requiring a complicated set-up for identifying the data to be charted.
A data source can be represented as a field list that contains a group of field icons. Each field icon represents a field that can be used to populate the chart. The charting DDUI is divided into drop zones. Dropping a field icon into a drop zone causes the charting DDUI to populate a corresponding portion of the chart with the data from the field. The field list is divided into two field groups: a values group and a characteristics group. The values group contains fields of actual data values (e.g., sales totals) and the characteristics group contains fields of data characteristics (e.g., regions in which those sales totals were accumulated).
A conventional charting DDUI has four drop zones. A Data Field drop zone accepts data fields from the values group, such as a “Sales” data field. A Category Field drop zone accepts category fields from the characteristics group, such as the “Region” category field. A Series Field drop zone accepts series fields from the characteristics group, such as a “Product” category field. Finally, a Filter Field drop zone accepts filter fields from the characteristics group, such as a “Month” category field.
Thus, the above-described drop zones can be used to generate a customized graphical representation of data. For example, an x-y chart could be generated, with regions listed along the x-axis, sales totals listed along the y-axis, with lines across the chart representing sales levels for various products. The Filter field could be used to limit the data charted to the last five years.
A user can chart data (i.e., generate a chart report) and then change the data to compare scenarios by dropping a new data field icon into the DDUI. Unfortunately, conventional charting DDUIs do not provide the ability to compare different data scenarios on the same screen. For example, if a user wanted to chart the above data, but also wanted to generate separate charts for retail stores and wholesale stores, the charts would have to be generated in sequence. That is, the user would have to generate a retail store chart and then generate a wholesale store chart, but could not display both charts at the same time. Therefore, there is a need in the art for a charting DDUI that can generate multiple charts at the same time and supports the drag-and-drop method of adding fields.